Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory
and an Application to Racial Justice

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Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice

16 October 2020

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Papers citing "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice"

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Title
Policy-Oriented Binary Classification: Improving (KD-)CART Final Splits for Subpopulation Targeting Lei Bill Wang Zhenbang Jiao Fangyi Wang 255 0 0 20 Feb 2025
Econometrics of Machine Learning Methods in Economic ForecastingSocial Science Research Network (SSRN), 2023 Andrii Babii Eric Ghysels Jonas Striaukas 182 5 0 21 Aug 2023
Policy Learning with Asymmetric Counterfactual UtilitiesJournal of the American Statistical Association (JASA), 2022 Eli Ben-Michael Kosuke Imai Zhichao Jiang OffRL 202 22 0 21 Jun 2022
Managers versus Machines: Do Algorithms Replicate Human Intuition in Credit Ratings? M. Harding Gabriel F. R. Vasconcelos AIFin 80 0 0 09 Feb 2022
Constrained Classification and Policy Learning T. Kitagawa Shosei Sakaguchi A. Tetenov OffRL 241 14 0 24 Jun 2021
Deep Learning for Individual Heterogeneity M. Farrell Tengyuan Liang S. Misra BDL 295 17 0 28 Oct 2020